“Do tech companies have to lower the bar to hire diverse candidates?”
Short story: No. Longer story: Here are a few reasons to stop asking that question, followed by a few alternatives to ask instead…
- The question assumes that there is some objective, apparently “God-given” bar that everyone agrees upon and upholds. If you have ever been on a hiring committee and are honest with yourself and others, you know that this is not the case. Sure, there are some general criteria or qualifications that are important. But, this seemingly “well-defined” set of criteria is always open to interpretation by the interviewer, and each interviewer’s assessment often varies.
Not to mention that this is further complicated by the fact that all of our assessments are subject to (yes, you guessed it) implicit biases. For example, looking for candidates that meet a “cultural fit” prioritizes impressions over skills. - Interview committees often rely on long-used criteria without asking whether all of these criteria are actually necessary for the job or whether some of these criteria may actually be unintentionally “weeding out” highly qualified talent. In other words, “the bar” is quite possibly bent out of shape from the get-go.
- Reams of research show that interviewers actually unintentionally raise the bar when it comes to hiring people from underrepresented groups. Study after study shows that women of color, white women, men of color, among others, need to have more qualifications to be ranked the same level of competency as white men.
Some people may answer the lowering-the-bar question with an anecdotal story about members from underrepresented groups being hired when they were not qualified for a job, but the research does NOT bear this out. It is of course possible that interviewers sometimes misapply diversity and inclusion advice and go on to hire someone unqualified. And, it is unfortunate if diversity and inclusion practices are misunderstood in this way, but this is the exception and NOT the rule.
Whenever someone offers such an anecdote, it is always worth asking: “So, how exactly do you know?” If the evidence is only hearsay or based on assumptions, more productive discussions should be had.
The next time that you hear the lowering-the-bar question, consider several better questions, which forward-thinking interview teams ask:
- Is the bar as good as believed?
- Is it getting at the actual qualifications for the job?
Is it applied consistently? - Might aspects of the current bar cause oversight of highly equipped talent that does not exactly fit preconceived notions?
In sum, questioning “the bar,” or the standards we use, is NOT the same as lowering it. Any good hiring process incorporates practices that mitigate gender and race-related bias by examining or changing criteria for resume selection, interviewing, etc. This evaluation process ensures that low or misguided criteria are kept in check and that the full range of skilled, qualified candidates are not missed.
Related Resources
- When it comes to recruitment, chapter six of NCWIT “Women in Tech: The Facts” identifies multiple steps that organizations can take to address bias, including rewriting job ads, expanding recruiting venues and strategies, analyzing interview questions and practices for potential biases, and auditing recruiting materials and physical office environment for potential biases.
- Common misunderstandings often surface when people talk about how to increase the participation of women in computing. Use the NCWIT “Critical Listening Guide” to learn how to spot the ‘red flags’ that indicate a particular discussion is headed in a direction that may not be research-based or effective.
- Companies can implement interview strategies that identify candidates with functionally diverse perspectives likely to improve innovation and productivity. Moving beyond traditional methods that value ‘highest scores,’ methods outlined in “Interview Strategies that Identify Functionally Diverse Perspectives (Case Study 1)” offer ways to identify and give credit for different kinds of approaches to problem-solving.